Formal synthesis of controllers for safety-critical autonomous systems: Developments and challenges
In recent years, formal methods have been extensively used in the design of autonomous
systems. By employing mathematically rigorous techniques, formal methods can provide …
systems. By employing mathematically rigorous techniques, formal methods can provide …
Probabilities are not enough: Formal controller synthesis for stochastic dynamical models with epistemic uncertainty
Capturing uncertainty in models of complex dynamical systems is crucial to designing safe
controllers. Stochastic noise causes aleatoric uncertainty, whereas imprecise knowledge of …
controllers. Stochastic noise causes aleatoric uncertainty, whereas imprecise knowledge of …
Safe policy synthesis in multi-agent POMDPs via discrete-time barrier functions
A multi-agent partially observable Markov decision process (MPOMDP) is a modeling
paradigm used for high-level planning of heterogeneous autonomous agents subject to …
paradigm used for high-level planning of heterogeneous autonomous agents subject to …
Unified multirate control: From low-level actuation to high-level planning
In this article, we present a hierarchical multirate control architecture for nonlinear
autonomous systems operating in partially observable environments. Control objectives are …
autonomous systems operating in partially observable environments. Control objectives are …
Perception-based temporal logic planning in uncertain semantic maps
In this article, we address a multi-robot planning problem in environments with partially
unknown semantics. The environment is assumed to have a known geometric structure (eg …
unknown semantics. The environment is assumed to have a known geometric structure (eg …
Multi-robot mission planning in dynamic semantic environments
This paper addresses a new semantic multi-robot planning problem in uncertain and
dynamic environments. Particularly, the environment is occupied with mobile and uncertain …
dynamic environments. Particularly, the environment is occupied with mobile and uncertain …
Counterexample-guided strategy improvement for pomdps using recurrent neural networks
We study strategy synthesis for partially observable Markov decision processes (POMDPs).
The particular problem is to determine strategies that provably adhere to (probabilistic) …
The particular problem is to determine strategies that provably adhere to (probabilistic) …
Point-based methods for model checking in partially observable Markov decision processes
Autonomous systems are often required to operate in partially observable environments.
They must reliably execute a specified objective even with incomplete information about the …
They must reliably execute a specified objective even with incomplete information about the …
Trust-aware motion planning for human-robot collaboration under distribution temporal logic specifications
Recent work has considered trust-aware decision making for human-robot collaboration
(HRC) with a focus on model learning. In this paper, we are interested in enabling the HRC …
(HRC) with a focus on model learning. In this paper, we are interested in enabling the HRC …
Barrier functions: Bridging the gap between planning from specifications and safety-critical control
Real-life control systems are hierarchies of interacting layers; often consisting of a planning
layer, a trajectory generation layer, and a trajectory-following layer. Independently designing …
layer, a trajectory generation layer, and a trajectory-following layer. Independently designing …